One of the key challenges facing any organization engaging in customer service is the maintenance of excellent outbound communications. Every customer service request becomes a two-way conversation in which the organization must assist their customer while maintaining an appropriate corporate tone. This is further complicated by organizations' reliance upon the conversational skills of their customer service representatives (CSRs), which may vary drastically from person to person. In written communication channels such as email or social media posts this problem manifests itself in many ways, ranging from simple spelling and grammatical mistakes to incorrect formality of language for a given situation. Disaffected CSRs may even send out intentionally unacceptable communications in response to communications from customers.
Employing common tools such as spelling and grammar checkers can mitigate some of these issues, but subtler issues often require application of quality assurance (QA) processes by the organization. Such processes require dedicated staff to double check outgoing messages for errors and appropriate tone. Either the QA staff or the original sender can then rectify mistakes or make other necessary changes before the message is sent on to the customer.
Maintaining a QA process like this can be costly to an organization. Inspecting individual messages is slow, delaying communication with customers. Smaller organizations cannot afford to set aside staff to look at every outbound communication. Larger organizations may have such a high volume of messages that a dedicated staff capable of handling the workload would be a significant drain on resources. This leads to inconsistent application of communication guidelines, sometimes ending in a poor experience for the customer. With the increase in online ratings and social media postings regarding customer experiences, publicized instances of poor communication can have a detrimental effect on a business.
There is an unmet need in the art for a system capable of automatically intercepting and analyzing outgoing messages sent from a CSR and rerouting poor-quality messages for correction.